Electromyography-controlled lower extremity exoskeleton to provide wearers flexibility in walking

Objective: In recent years, there have been significant developments in lower extremity robotic exoskeletons intended for gait rehabilitation. However, wearers may not be sufficiently motivated to participate in traditional rehabilitation robot training as the training pattern is usually predefined and rigid. Enabling wearers to actively control the exoskeleton to assist them in walking may improve rehabilitation treatments. Methods: This paper presents an electromyography (EMG)-based gait pattern adaptation method that allows subjects to control the exoskeleton via EMG signals of thigh muscles (quadriceps femoris and hamstrings muscles). Six healthy subjects participated in the initial experiment on a treadmill based lower extremity rehabilitation robot system. In a single walking routine, six widely used adaptation gait patterns were tested. Results: The results indicate that all of the subjects were able to change the gait pattern of the exoskeleton and achieved the adaptation goals stably within average 16 strides by generating EMG signals. The muscle activation during the adaptation condition is significantly higher than that in fixed normal walking condition (p < 0.05). The subjects gave positive evaluation on the designed system. Conclusion: With this method, the subjects were involved in the control loop and actively participated in the training. Significance: The proposed EMG-based two-layer admittance control algorithm is novel, which enabled subjects to adjust gait trajectories continuously and smoothly.